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Research on network coding aware energy efficient routing for wireless sensor networks

delete2018-10-01
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Xing Shao *
C
Cuixiang Wang
J
Jun Gao
DOI:10.1186/s13638-018-1245-8delete
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摘要

摘要

En 中文
Wireless sensor nodes in wireless sensor networks are generally battery powered and it is usually hard to change their batteries. Therefore, energy saving has always been the basic critical problem of wireless sensor networks. In recent years, network coding has become a promising technology to improve network throughput, reduce transmission number, and save energy, which has great potential to solve the energy efficiency problem of wireless sensor networks. In addition, some network coding aware routings have been proposed. However, the network coding condition of existing network coding aware routings may experience the problem of false-coding effect in some scenarios, and usually neglect node energy, which greatly influences the energy efficiency performance. Therefore, existing network coding aware routings are not suitable for wireless sensor networks. This paper proposes network coding aware energy efficient routing (NAER) for wireless sensor networks. In NAER, universal network coding condition is presented and proved to avoid false-coding problem. Besides, combined with the coverage control and topology control mechanism at lower layer, cross layer coding opportunity discover mechanism is presented to increase coding opportunities. In addition, a network coding aware energy efficient routing metric (NERM) is presented, which takes coding opportunity, node energy, and link quality into account jointly. Simulation results demonstrate that NAER improves the accuracy of coding discovery mechanism, increases the number of coding opportunities, saves node's energy consumption, and prolongs network lifetime.
Keyword:
Network coding aware
Energy efficient
Routing algorithm
Wireless sensor networks
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期刊

EURASIP Journal on Wireless Communications and Networking 封面图
EURASIP Journal on Wireless Communications and Networking
IF:
1.9
论文数:
161
被引数:
3.6K

机构

Y
Yancheng Institute of Technology
学者数:
4.3K
论文数: 3.2K
被引数: 5.5K
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引用论文

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